Background knowledge guided characterization positioning privacy anti-leakage method

Abstract

According to a background knowledge guided characterization positioning privacy anti-leakage method provided by the invention, different levels of privacy anti-leakage services can be provided according to characterization requirements of users. When the users share the positioning information with each other, the precise positions of the users are no longer shared, instead, a meticulously calculated hybrid region is adopted to replace the real positions of the users. According to the invention, the balance is comprehensively considered from two aspects of privacy protection effect and user experience, the area of the hybrid region is small, and the number of users contained in the hybrid region is as large as possible, therefore, the users can enjoy various convenience and services provided by a positioning service application while the private information of the users is not leaked, the method is one of the methods for solving the problem of leakage of the private information of thepositioning service and achieving the optimal comprehensive effect, and the method has huge application and popularization values and a wide market space.

Description

technical field [0001] The invention relates to a positioning privacy anti-disclosure method, in particular to a background knowledge-guided characteristic positioning privacy anti-disclosure method, which belongs to the technical field of user positioning privacy protection. Background technique [0002] With the widespread use of smart phones all over the world, the mobile Internet is showing a blowout development trend. People eagerly hope that they can easily obtain all kinds of information they need from the Internet anytime, anywhere, even when they are constantly moving. Various services. With the large-scale popularization of the mobile Internet, users can connect to the Internet through various handheld positioning devices anytime, anywhere. The Internet is more closely connected with people's lives, and users can better enjoy the many conveniences brought by the Internet. The biggest difference between the mobile Internet and the traditional Internet is that it ha...

AI Technical Summary

Problems solved by technology

[0014] The third is that the anti-leakage target of the anonymity and pseudonym technology in the prior art is the online identity of the user. With the continuous advancement of data mining technology, location stealers can already use data mining technology to obtain the user’s private information, so only using Pseudonym technology to disguise user's private information is no longer safe

In the prior art, if the range of false addresses selected is large, it will affect the quality of the user's application service, but if the range of false addresses is too small, the user's real location cannot be well protected, so the method of preventing privacy leakage of false addresses The difficulty lies in how to balance the contradiction between positioning privacy and user experience.

[0015] Fourth, the existing privacy and location-based anti-leakage models all use a trusted third party to complete the user’s anonymity process. However, in geographical locations where users are relatively sparse, an excessively large fuzzy area will be generated, resulting in the loss of user Experience severely degraded

The existing technology of user collaboration without anonymous area location privacy anti-leakage method adopts a system structure without a central server, and does not need to use a third party to complete the anonymity process, but this method requires joint cooperation among users. Otherwise, the credibility among users will be difficult to guarantee, and the privacy security of other users will also be threatened

[0016] Fifth, the existing K-anonymity technology cannot meet the user's location privacy and anti-leakage requirements. In the release, more research energy is still needed to come up with a better method. Second, K-anonymity technology obtains data privacy protection by reducing data quality, making it impossible to obtain high-quality data and very safe privacy at the same time. The protection effect is difficult to balance the contradiction between the two. The third is that location privacy protection in different scenarios is also a new requirement. Users need different degrees of protection against their own information in different scenarios. The fourth is K-anonymity Technology requires a reliable third party, that is, an anonymizer in the location service application using a server structure. The current development of anonymizers has become a bottleneck in the promotion of this technology in the field of location services. Anonymizers are easy to become the target of location stealers. Once the anonymizer If it is cracked by a location stealer, the user's private information and location information will be leaked. Fifth, in the point-to-point location service application, although the location service application in the server structure mode does not need to integrate a reliable third party, it needs to be completed on the user side. Anonymous calculation will lead to excessive calculation pressure on the user end. If malicious location stealers are mixed into the user group, it will also lead to the leakage of user privacy information and pose a major threat to user security.

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